Astor Torano Caicoya

Boreal forest biomass classification with TanDEM-X

High spatial resolution X-band interferometric SAR data from the TanDEM-X, in the operational DEM generation mode, are sensitive to forest structure and can therefore be used for thematic boreal forest classification of forest environments. The interferometric coherence in absence of temporal decorrelation depends strongly on forest height and structure. Due to the rather homogenous structure of boreal forest, forest biomass can be derived from forest height, on the basis of allometric equations with sufficient accuracy to be used for thematic classification applications. Two test sites in mid- and southern Sweden are investigated. A maximum of 4 biomass classes, up to 250 Mg/ha, are achieved. Larger spatial baselines result in better classification performances.

Large Scale Biomass Classification in Boreal Forests with TanDEM-X Data

Boreal forests are characterized by a rather homogeneous stand structure that allows by means of a single allometric equation to estimate biomass from forest height with sufficient accuracy and, therefore, to use this equation for quantitative biomass classifications. In this paper, interferometric TanDEM-X DEM data are used to estimate forest height over boreal forest systems. The accuracy of the height inversion is evaluated for single-and dual-baseline scenarios, under summer and winter conditions. Then, an allometric equation is used to transfer forest height to biomass. For this, two forest sites, boreal (Krycklan) and hemiboreal (Remningstorp) in north and southern Sweden, respectively, are investigated. A performance analysis is carried out to estimate the maximum number of biomass classes obtained, depending on the height estimation accuracy. For summer acquisitions, four biomass classes can be obtained, with a maximum biomass class of > 200 Mg/ha. For winter acquisitions or when a mixed summer-winter approach is applied, five biomass classes, up to 220 Mg/ha, can be obtained. This classification shows a good agreement with CORINE, an existing land cover classification, and can improve it by adding quantitative forest biomass classes with a high spatial resolution of 16 × 16 m.

Forest Above-Ground Biomass Estimation From Vertical Reflectivity Profiles at L-Band

Forest height is an important parameter for the allometric estimation of above-ground forest biomass (AGB). However, variable forest stand densities limit the performance of the allometric estimation of AGB from height measurements alone. Recently, the use of vertical forest structure information as an indicator for the variation of stand density has been proposed and used to improve the allometric estimation of AGB from height measurements. In this letter, the use of vertical radar reflectivity profiles at L-band obtained from SAR tomography, as a proxy for vertical forest structure for the allometric estimation of AGB, is investigated. L-band reflectivity profiles, which are reconstructed from data at different polarizations (HH and HV) and acquired under “moist” and “dry” weather conditions, are investigated. The proposed allometric AGB estimator increases the correlation factor from 0.60 to 0.81 and reduces the root-mean-square error from 50.25 to 36.30 Mg/ha when compared with the AGB estimation from forest height alone. The effect of polarization and weather conditions on the AGB estimation performance is discussed.

Vertical forest structure characterization for the estimation of above ground biomass: First experimental results using SAR vertical reflectivity profiles

One common method to estimate biomass is measuring forest height and applying allometric equations to get forest biomass. However, changing forest density or forest structure bias the known allometric relations. Remote sensing systems like SAR or LIDAR allow to measure vertical forest structure. In this paper the value of vertical forest structure information for biomass inversion is investigated. First, vertical biomass profiles are calculated from forest inventory data. Then, a vertical structure descriptor based on Legendre polynomials is suggested and its sensitivity to biomass is evaluated. In a second step, this descriptor is used to describe SAR vertical reflectivity profiles. Then, a biomass estimation algorithm is developed. This is a case study based on inventory data from the Traunstein test site, a temperate mixed forest, located in the southeast of Germany.

Forestry projections for species diversity-oriented management: an example from Central Europe

IntroductionChanges in socio-economy and climate are affecting the demand of wood products globally. At the same time, society requires that forest supporting structures like biodiversity are maintained and preserved while the demand for wood products is also covered. Management support systems, like forest simulation models, that are able to analyze connections as well as quantify trade-offs between forest structure management and biodiversity indicators are highly sought. However, such models are generally developed for the local plot or stand scale only and ecosystem-scale analyses are missing. In this study, we analyzed ways to interpret results from the single-tree forest simulator SILVA from the local to the ecosystem scale. We also analyzed the impacts of forest management on biodiversity using two species diversity indicators, the species profile index and the species intermingling, for scenarios adapted from the GLOBIOM model in the case study “Augsburg Western Forests”, a high productive region in South-Germany. In order to evaluate diversity tendencies across the ecosystem, we applied a moving window methodology.ResultsThe relevance of scale for the interpretation of management effects on species diversity was shown and clear differences between scenarios revealed. The differences between scenarios were particularly visible when comparing the two diversity indicators, especially because the species profile index focuses on vertical and horizontal information and the species intermingling focuses mainly on horizontal structures. Under a multifunctional scenario, biodiversity values could be preserved at all scales in the vertical dimension. However, under a bio-energy-oriented scenario diversity at the local scale was reduced, although at the ecosystem level, and only in the horizontal dimension, diversity remained at relatively high values.ConclusionsWith this work, we can conclude that integrative modeling, with multiple scenarios, is highly needed to support forestry decision making and towards the evolution of forest management to consider the ecosystem scale, especially when the optimization of diversity is a management priority.